MongoDB with pyMongo III - Range Querying

List of MongoDB with PyMongo

1. MongoDB with PyMongo I - Installing MongoDB
2. MongoDB with PyMongo II - Connecting and accessing MongoDB
3. MongoDB with pyMongo III - Range Querying MongoDB
4. MongoDB RESTful API with Flask

Here is the current code for this chapter:

# mongo3.py

from pymongo import MongoClient

client = MongoClient('mongodb://localhost:27017/')
mydb = client['test-database']

mydb.posts.drop()

import datetime
post = {
        "author": "Duke 5",
        "title" : "PyMongo 101 - 5",
        "tags" : ["MongoDB 5", "PyMongo 101 - A5", "Tutorial 5"],
        "date" : datetime.datetime.utcnow()
        }

posts = mydb.posts
post_id = posts.insert(post)

print post_id
print mydb.collection_names()

new_posts = [{"author": "Duke 6",
              "title" : "PyMongo 101-A6",
              "tags" : ["MongoDB 6", "PyMongo 6", "Tutorial 6"],
              "date" : datetime.datetime(2015, 11, 28, 01, 13)},
             {"author": "Adja",
              "title": "MongoDB 101-A7",
              "note": "Schema free MongoDB",
              "date": datetime.datetime(2015, 11, 29, 11, 42)}
            ]
mydb.posts.insert(new_posts)

To get more than a single document as the result of a query we use the find() method. find() returns a Cursor instance, which allows us to iterate over all matching documents. For example, we can iterate over every document in the mydb.posts collection after running the code of the previous section:

>>> for post in mydb.mytable.find():
...    post
... 
{u'date': datetime.datetime(2015, 11, 28, 5, 18, 40, 945000), u'_id': ObjectId('5659393d312f910b5b05c18a'), u'author': u'Duke', u'tags': [u'MongoDB', u'PyMongo', u'Tutorial'], u'title': u'PyMongo 101'}
{u'date': datetime.datetime(2015, 11, 28, 6, 11, 6, 496000), u'_id': ObjectId('5659457a312f91162bf20276'), u'author': u'Duke II', u'tags': [u'MongoDB II', u'PyMongo II', u'Tutorial II'], u'title': u'PyMongo II 101'}
{u'date': datetime.datetime(2015, 11, 28, 6, 11, 6, 496000), u'_id': ObjectId('5659457a312f91162bf20277'), u'author': u'Duke III', u'tags': [u'MongoDB III', u'PyMongo III', u'Tutorial III'], u'title': u'PyMongo III 101'}
{u'date': datetime.datetime(2015, 11, 28, 7, 2, 37, 317000), u'_id': ObjectId('56595481312f9119e4bace31'), u'author': u'Duke 4', u'tags': [u'MongoDB 4', u'PyMongo 4', u'Tutorial 4'], u'title': u'PyMongo 4 101'}
...

We can pass a document to find() to limit the returned results. Here, we get only those documents whose author is "Adja":

>>> for post in mydb.mytable.find({"author": "Adja"}):
...    post
... 
{u'note': u'Schema free MongoDB', u'date': datetime.datetime(2015, 11, 29, 11, 42), u'_id': ObjectId('56595cf0312f912bc242f79e'), u'author': u'Adja', u'title': u'MongoDB 101-A7'}
>>> 

When we just want to know how many documents match a query, we can perform a count() operation instead of a full query:

>>> mydb.mytable.count()
7

>>> mydb.mytable.find({"author": "Adja"}).count()
1

Let's perform a query where we limit results to posts older than a certain date, but also sort the results by author:

>>> import datetime
>>> for post in mydb.mytable.find({"date": {"$lt": datetime.datetime(2015, 12, 1)}}).sort("author"):
...    post
... 
{u'note': u'Schema free MongoDB', u'date': datetime.datetime(2015, 11, 29, 11, 42), u'_id': ObjectId('56595cf0312f912bc242f79e'), u'author': u'Adja', u'title': u'MongoDB 101-A7'}
{u'date': datetime.datetime(2015, 11, 28, 5, 18, 40, 945000), u'_id': ObjectId('5659393d312f910b5b05c18a'), u'author': u'Duke', u'tags': [u'MongoDB', u'PyMongo', u'Tutorial'], u'title': u'PyMongo 101'}
...

List of MongoDB with PyMongo

1. MongoDB with PyMongo I - Installing MongoDB
2. MongoDB with PyMongo II - Connecting and accessing MongoDB
3. MongoDB with pyMongo III - Range Querying MongoDB
4. MongoDB RESTful API with Flask